Hyperscale computing involves distributed computing environments (for example, a “cloud” computing environment) developed to scale exponentially, typically to hundreds or thousands of servers. Data centers employing hyperscale platforms require vast amounts of telemetry data and face substantive scalability issues. The telemetry processes in such environments require fast responsiveness and high polling rates. Accordingly, an increase in the number of monitored entities in a data center results in a proportional increase in, for example, the amount of data transferred to a corresponding controller, the processing cycles spent handling the data, or the amount of storage necessary to store the monitored data for post-processing and future analysis. With hyperscale data centers, such increases in resource and storage requirements may occur exponentially, resulting in scalability challenges.